Glycated proteome: From reaction to intervention

Glycation, a nonenzymatic reaction between reducing sugars and proteins, is a proteome wide phenomenon, predominantly observed in diabetes due to hyperglycemia. Glycated proteome of plasma, kidney, lens, and brain are implicated in the pathogenesis of various diseases, including diabetic complications, neurodegenerative diseases, cancer, and aging. This review discusses the strategies to characterize protein glycation, its functional implications in different diseases, and intervention strategies to protect the deleterious effects of protein glycation.     

Spatio-temporal polygonal clustering with space and time as first-class citizens

Detecting spatio-temporal clusters, i.e. clusters of objects similar to each other occurring together across space and time, has important real-world applications such as climate change, drought analysis, detection of outbreak of epidemics (e.g. bird flu), bioterrorist attacks (e.g. anthrax release), and detection of increased military activity. Research in spatio-temporal clustering has focused on grouping individual objects with similar trajectories, detecting moving clusters, or discovering convoys of objects. However, most of these solutions are based on using a piece-meal approach where snapshot clusters are formed at each time stamp and then the series of snapshot clusters are analyzed to discover moving clusters. This approach has two fundamental limitations. First, it is point-based and is not readily applicable to polygonal datasets. Second, its static analysis approach at each time slice is susceptible to inaccurate tracking of dynamic cluster especially when clusters change over both time and space. In this paper we present a spatio-temporal polygonal clustering algorithm known as the Spatio-Temporal Polygonal Clustering (STPC) algorithm. STPC clusters spatial polygons taking into account their spatial and topological properties, treating time as a first-class citizen, and integrating density-based clustering with moving cluster analysis. Our experiments on the drought analysis application, flu spread analysis and crime cluster detection show the validity and robustness of our algorithm in an important geospatial application.     

Assessing Decentralised Water Solutions: Towards a Framework for Adaptive Learning

This paper reports on the use of qualitative analysis to inform a risk analysis framework for decentralised water systems. To realise the benefits from these technologies, a methodology is applied to learn from previous difficulties in implementing and managing them. A workshop process was used to capture stories from industry professionals on difficulties they have encountered in planning and implementation. Qualitative analysis of story narratives revealed stages where there was some type of development process failure; as well as failure modes and factors influencing the difficulties encountered. The analysis also generated insights: difficulties in one part of the development process tends to propagate to subsequent stages; system difficulties most often occurred in the policy stage of development due to institutional inertia and lack of adaptive governance; and the best indicator of problems with a decentralised system was complaints of poor water quality. Furthermore, this paper also provides a method to learn from past difficulties by identifying what data needs to be collected in order to populate a risk model which can be used for improving risk assessment of the development process for decentralised systems. This can provide a basis for better decision making, policy and guidelines; an important factor in mainstream acceptance.     

Multi-objective optimization in wire-electro-discharge machining of TiC reinforced composite through Neuro-Genetic technique

This paper proposed a Neuro-Genetic technique to optimize the multi-response of wire electro-discharge machining (WEDM) process. The technique was developed through hybridization of a radial basis function network (RBFN) and non-dominated sorting genetic algorithm (NSGA-II). The machining was done on 5 vol% titanium carbide (TiC) reinforced austenitic manganese steel metal matrix composite (MMC). The proposed Neuro-Genetic technique was found to be potential in finding several optimal input machining conditions which can satisfy wide requirements of a process engineer and help in efficient utilization of WEDM in industry.     

Polyelectrolyte multilayers for bio‐applications: recent advancements

The synergistic relationship between structure and the bulk properties of polyelectrolyte multilayer (PEM) films has generated tremendous interest in their application for loading and release of bioactive species. Layer‐by‐layer assembly is the simplest, cost effective process for fabrication of such PEMs films, leading to one of the most widely accepted platforms for incorporating biological molecules with nanometre precision. The bulk reservoir properties of PEM films render them a potential candidate for applications such as biosensing, drug delivery and tissue engineering. Various biomolecules such as proteins, DNA, RNA or other desired molecules can be incorporated into the PEM stack via electrostatic interactions and various other secondary interactions such as hydrophobic interactions. The location and availability of the biological molecules within the PEM stack mediates its applicability in various fields of biomedical engineering such as programmed drug delivery. The development of advanced technologies for biomedical applications using PEM films has seen rapid progress recently. This review briefly summarises the recent successes of PEM being utilised for diverse bio‐applications.Inspec keywords: polymer electrolytes, multilayers, polymer films, molecular biophysics, biomedical materials, biochemistryOther keywords: bioapplications, polyelectrolyte multilayer films, bioactive species, layer‐by‐layer assembly, biological molecules, biosensing, drug delivery, tissue engineering, biomolecules, proteins, DNA, RNA, electrostatic interactions, secondary interactions, hydrophobic interactions, biomedical engineering, programmed drug delivery, biomedical applications, PEM films     

A multisource energy harvesting utilizing highly efficient ferroelectric PMN-PT single crystal

This paper demonstrates a multi-source energy harvester that is able to utilize simultaneously both piezoelectric and pyroelectric effects in lead magnesium niobate-lead titanate (PMN-PT) single crystal. The paper presents a study of PMN-PT single crystal with a (67:33) composition grown in our laboratory via a vertical gradient freeze method without any flux. The performance of the piezoelectric and pyroelectric energy harvester using unimorph device structure was evaluated via modeling and experiment. The theoretical study was implemented based on a distributed parameter electromechanical model and the modelling procedure was approximated using finite element analysis to predict the electromechanical behavior of the harvester. The maximum power density at a resonance frequency of 50 Hz and optimum resistance of 2 MΩ was 16.7 nW/(g² cm³) under a 1 g acceleration of vibration. The measured values of electrical output parameters were in good agreement with theoretical and modelling results using MATLAB and COMSOL Multiphysics, respectively. By using the pyroelectric effect along with the piezoelectric effect, the output voltage of the energy harvester was found to be enhanced at the optimum resistance and specific frequency values. It was noticed that the output voltage was increased monotonically with temperature-difference (ΔT) and reaches up to 180 % of its original value under temperature difference of 1.7 °C at a frequency value of 49 Hz.     

Valve controlled fluorescence detection system for remote sensing applications

We demonstrate a microfluidics-based fluorescence detection device where the filters, source, detector, and electronically controlled valves are embedded into a Polydimethylsiloxane (PDMS)-based microfluidic chip. The device reported here has been specifically designed for chlorophyll a fluorescence sensing in autonomous systems, such as oceanic applications. In contrast to a monolithic approach, the modular approach made the fabrication of this device simpler and cheaper. For fluorescence detection, an InGaN/GaN LED is used as the excitation source to specifically excite chlorophyll a; a metal-dielectric Fabry?CPerot filter was used to extinguish out-of-band excitation. A simple Si photodiode is used as detector and provided with a thermally evaporated CdS emission filter to block the excitation source. This filter combination provides an excellent solution to the difficult problem of combining high-rejection excitation and emission filters in an integrated thin-film format. Furthermore, the metal-dielectric filter provides a much broader angular response than a comparable multilayer Bragg mirror, which is a key advantage in the integrated format. We use a novel paraffin wax-based valve design affords low power single-use actuation, between 0.5 and 1 J per actuation and withstands 0.6 bar differential pressure, which provides better performance than its previously reported counterparts. The remote valve-controlled operation of the fluorescence detection system is demonstrated, illustrating the measurement of a chlorophyll a solution, with a detection limit of 340 ??M and subsequent valve-controlled flushing of the measurement reservoir.     

Reinterpretable Imager: Towards Variable Post‐Capture Space,Angle and Time Resolution in Photography

We describe a novel multiplexing approach to achieve tradeoffs in space, angle and time resolution in photography. We explore the problem of mapping useful subsets of time‐varying 4D lightfields in a single snapshot. Our design is based on using a dynamic mask in the aperture and a static mask close to the sensor. The key idea is to exploit scene‐specific redundancy along spatial, angular and temporal dimensions and to provide a programmable or variable resolution tradeoff among these dimensions. This allows a user to reinterpret the single captured photo as either a high spatial resolution image, a refocusable image stack or a video for different parts of the scene in post‐processing. A lightfield camera or a video camera forces a‐priori choice in space‐angle‐time resolution. We demonstrate a single prototype which provides flexible post‐capture abilities not possible using either a single‐shot lightfield camera or a multi‐frame video camera. We show several novel results including digital refocusing on objects moving in depth and capturing multiple facial expressions in a single photo.     

Low cycle fatigue,fatigue crack propagation and substructures in a series of polycrystalline Cu-Al alloys

Low Cycle Fatigue (LCF) on smooth hour glass specimens and Fatigue Crack Propagation (FCP) studies on Single Edge Notch (SEN) specimens were carried out at room temperature on four Cu-Al polycrystalline alloys to investigate the effects of Stacking Fault Energy (SFE) and mechanical property variations on fatigue characteristics. Significant improvements in fatigue properties were observed for alloys of low SFE. A microhardness technique was used to delineate the fatigue plastic zone ahead of stopped cracks at several stress intensity ranges for all the alloys. Planar slip was associated with a less than a second power dependence of plastic zone size on the stress intensity range. Transmission Electron Microscopy (TEM) was used to observe the substructures that developed both in LCF at different strain ranges and also ahead of fatigue cracks at different stress intensity ranges. Fractography was carried out to study the micromechanisms of crack propagation using a two stage replication technique. The experimental results were in good agreement with a theoretical model for FCP developed previously by the authors which incorporates mechanical and microstructural variables.     

Competitiveness and an Emerging Sector: The Russian Software Industry and its Global Linkages

This paper analyzes the Russian software industry in the context of trade in information technology services. We assess Russia's underlying sources of competitive edge in software, such as its scientific establishments, education system, diaspora and low costs, and identify the institutional impediments to growth. A survey reveals that foreign outsourcing contracts, a high value-added niche and high education levels characterize Russia's small, privately held software firms. A comparison with the Indian software industry underscores the structural differences in outsourcing relationships developed by the two countries and emphasizes that national advantages are complex amalgamations of many factors and need to be overtly marketed. Beyond the resources that give comparative and competitive advantage to a transitioning economy, a critical role is played by powerful industry organizations and by non-market state institutions that can level the economic field and inject credibility into market structures.